基于深度学习的偏差补偿提高了光显微镜中的对比度和分辨率

Min Guo1,2, Yicong Wu3,4,5, Chad M Hobson6

  • 1State Key Laboratory of Extreme Photonics and Instrumentation, College of Optical Science and Engineering, Zhejiang University, Hangzhou, China. guom@zju.edu.cn.

Nature communications
|January 3, 2025
PubMed
概括

这项研究引入了一种深度学习方法,用于纠正光显微镜中的光学偏差,提高图像质量,无需额外的硬件或辐射. 该技术改善了生物样本的图像分析,有助于进行血管分析和细胞细分等任务.

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